306 pages, 50 black & white illustrations
Created for advanced undergraduates in computer science programs, "Biological Computation" covers major themes of bio-inspired computing, including cellular automata, molecular computation, genetic algorithms, and neural networks. Providing theoretical and coding exercises, this self-contained text requires no previous knowledge of biology. The book provides valuable insight to researchers and students from biomedical backgrounds looking to gain the computational skills needed to make entry into the fields of systems biology, biological modeling, and simulations.
Biological computing, the three-billion-year-old goldmine of information processing concepts, is ready for our educational mainstream. This beautiful undergraduate text by Lamm and Unger may be the first step. This book expertly presents fundamental concepts of molecular biology in its first chapter, and then goes on to develop many computing classics from biology. ! I enjoyed reading this text. The exercises flex the imagination, the definitions are clear and precise, and the explanations are unusually powerful. I have been searching for a text like this for years, and now I look forward to using it. --Computing Reviews, August 2011 I read this book in one breath--it opens vistas on how the fields of computation and biology can inspire each other. I particularly enjoyed the analogies between immune systems and software that fights computer viruses. --Uri Alon, Weizmann Institute of Science, Rehovot, Israel, and author of An Introduction to Systems Biology: Design Principles of Biological Circuits The book by Lamm and Unger methodically covers exciting developments in biological computation, offering for the first time a broad perspective of this important cutting-edge field of research. --Ehud Shapiro, The Harry Weinrebe Professorial Chair of Computer Science and Biology, Weizmann Institute of Science, Rehovot, Israel This is a wonderful treatise on bio-inspired computation, written from a computer science perspective. The authors are extremely knowledgeable about their subject, and the material they cover is both broad and deep. The book should benefit anyone interested in the connection between computer science and biology, a connection that is poised to become dramatically central to the science of the 21st century. --David Harel, The William Sussman Professorial Chair, Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel
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